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Merge branch 'main' into bbq_hnsw-disk-rescoring
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‎.buildkite/scripts/generate-pr-performance-benchmark.sh‎

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CONFIGURATION_NAME: ${GITHUB_PR_COMMENT_VAR_BENCHMARK}
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ENV_ID: ${env_id_baseline}
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REVISION: ${merge_base}
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BENCHMARK_TYPE: baseline
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- label: Trigger contender benchmark with ${GITHUB_PR_TRIGGERED_SHA:0:7}
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trigger: elasticsearch-performance-esbench-pr
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build:
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ENV_ID: ${env_id_contender}
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ES_REPO_URL: https://github.com/${GITHUB_PR_OWNER}/${GITHUB_PR_REPO}.git
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REVISION: ${GITHUB_PR_TRIGGERED_SHA}
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BENCHMARK_TYPE: contender
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- wait: ~
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- label: Update PR comment and Buildkite annotation
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command: |

‎.gitignore‎

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**/.local*
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.vagrant/
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/logs/
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**/target/
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# osx stuff
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.DS_Store

‎benchmarks/src/main/java/org/elasticsearch/benchmark/bytes/RecyclerBytesStreamOutputBenchmark.java‎

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package org.elasticsearch.benchmark.bytes;
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import org.apache.lucene.util.BytesRef;
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import org.elasticsearch.benchmark.common.util.UTF8StringBytesBenchmark;
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import org.elasticsearch.common.io.stream.RecyclerBytesStreamOutput;
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import org.elasticsearch.common.recycler.Recycler;
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import org.openjdk.jmh.annotations.Benchmark;
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// We use weights to generate certain sized UTF-8 characters and vInts. However, there is still some non-determinism which could
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// impact direct comparisons run-to-run
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shortString = generateAsciiString(20);
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longString = generateAsciiString(100);
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nonAsciiString = generateUtf8String(200);
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veryLongString = generateAsciiString(800);
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shortString = UTF8StringBytesBenchmark.generateAsciiString(20);
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longString = UTF8StringBytesBenchmark.generateAsciiString(100);
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nonAsciiString = UTF8StringBytesBenchmark.generateUTF8String(200);
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veryLongString = UTF8StringBytesBenchmark.generateAsciiString(800);
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// vint values for benchmarking
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vints = new int[1000];
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for (int i = 0; i < vints.length; i++) {
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}
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}
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public static String generateAsciiString(int n) {
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ThreadLocalRandom random = ThreadLocalRandom.current();
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StringBuilder sb = new StringBuilder(n);
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for (int i = 0; i < n; i++) {
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int ascii = random.nextInt(128);
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sb.append((char) ascii);
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}
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return sb.toString();
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}
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public static String generateUtf8String(int n) {
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ThreadLocalRandom random = ThreadLocalRandom.current();
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StringBuilder sb = new StringBuilder(n);
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for (int i = 0; i < n; i++) {
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int codePoint;
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int probability = random.nextInt(100);
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if (probability < 85) {
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// 1-byte UTF-8 (ASCII range)
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// 0x0000 to 0x007F
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codePoint = random.nextInt(0x0080);
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} else if (probability < 95) {
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// 2-byte UTF-8
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// 0x0080 to 0x07FF
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codePoint = random.nextInt(0x0080, 0x0800);
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} else {
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// 3-byte UTF-8
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// 0x0800 to 0xFFFF
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do {
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codePoint = random.nextInt(0x0800, 0x10000);
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// Skip surrogate pairs (0xD800-0xDFFF)
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} while (codePoint >= 0xD800 && codePoint <= 0xDFFF);
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}
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sb.appendCodePoint(codePoint);
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}
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return sb.toString();
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}
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private record BenchmarkRecycler(AtomicReference<BytesRef> bytesRef) implements Recycler<BytesRef> {
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@Override

‎benchmarks/src/main/java/org/elasticsearch/benchmark/common/util/UTF8StringBytesBenchmark.java‎

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/*
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* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
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* or more contributor license agreements. Licensed under the "Elastic License
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* 2.0", the "GNU Affero General Public License v3.0 only", and the "Server Side
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* Public License v 1"; you may not use this file except in compliance with, at
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* your election, the "Elastic License 2.0", the "GNU Affero General Public
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* License v3.0 only", or the "Server Side Public License, v 1".
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*/
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package org.elasticsearch.benchmark.common.util;
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import org.apache.lucene.util.BytesRef;
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import org.apache.lucene.util.UnicodeUtil;
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import org.elasticsearch.common.UUIDs;
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import org.openjdk.jmh.annotations.Benchmark;
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import org.openjdk.jmh.annotations.BenchmarkMode;
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import org.openjdk.jmh.annotations.Fork;
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import org.openjdk.jmh.annotations.Measurement;
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import org.openjdk.jmh.annotations.Mode;
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import org.openjdk.jmh.annotations.OutputTimeUnit;
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import org.openjdk.jmh.annotations.Param;
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import org.openjdk.jmh.annotations.Scope;
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import org.openjdk.jmh.annotations.Setup;
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import org.openjdk.jmh.annotations.State;
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import org.openjdk.jmh.annotations.Warmup;
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import java.nio.ByteBuffer;
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import java.nio.charset.StandardCharsets;
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import java.util.concurrent.ThreadLocalRandom;
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import java.util.concurrent.TimeUnit;
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@Warmup(iterations = 3)
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@Measurement(iterations = 3)
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@BenchmarkMode(Mode.AverageTime)
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@OutputTimeUnit(TimeUnit.NANOSECONDS)
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@Fork(value = 1)
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public class UTF8StringBytesBenchmark {
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@State(Scope.Thread)
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public static class StringState {
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@Param({ "uuid", "short", "long", "nonAscii", "veryLong" })
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String stringType;
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String string;
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BytesRef bytes;
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@Setup
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public void setup() {
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string = switch (stringType) {
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case "uuid" -> UUIDs.base64UUID();
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case "short" -> generateAsciiString(20);
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case "long" -> generateAsciiString(100);
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case "nonAscii" -> generateUTF8String(200);
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case "veryLong" -> generateAsciiString(1000);
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default -> throw new IllegalArgumentException("Unknown stringType: " + stringType);
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};
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bytes = getBytes(string);
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}
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}
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@Benchmark
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public BytesRef getBytesJDK(StringState state) {
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byte[] bytes = state.string.getBytes(StandardCharsets.UTF_8);
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return new BytesRef(bytes, 0, bytes.length);
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}
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@Benchmark
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public BytesRef getBytesUnicodeUtils(StringState state) {
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String string = state.string;
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int length = string.length();
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int size = UnicodeUtil.calcUTF16toUTF8Length(string, 0, length);
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byte[] out = new byte[size];
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UnicodeUtil.UTF16toUTF8(string, 0, length, out, 0);
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return new BytesRef(out, 0, out.length);
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}
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@Benchmark
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public BytesRef getBytesByteBufferEncoder(StringState state) {
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var byteBuff = StandardCharsets.UTF_8.encode(state.string);
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assert byteBuff.hasArray();
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return new BytesRef(byteBuff.array(), byteBuff.arrayOffset() + byteBuff.position(), byteBuff.remaining());
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}
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@Benchmark
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public String getStringJDK(StringState state) {
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BytesRef bytes = state.bytes;
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return new String(bytes.bytes, bytes.offset, bytes.length, StandardCharsets.UTF_8);
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}
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@Benchmark
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public String getStringByteBufferDecoder(StringState state) {
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BytesRef bytes = state.bytes;
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var byteBuff = ByteBuffer.wrap(bytes.bytes, bytes.offset, bytes.length);
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return StandardCharsets.UTF_8.decode(byteBuff).toString();
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}
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private static BytesRef getBytes(String string) {
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int before = ThreadLocalRandom.current().nextInt(0, 50);
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int after = ThreadLocalRandom.current().nextInt(0, 50);
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byte[] stringBytes = string.getBytes(StandardCharsets.UTF_8);
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byte[] finalBytes = new byte[before + after + stringBytes.length];
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System.arraycopy(stringBytes, 0, finalBytes, before, stringBytes.length);
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return new BytesRef(finalBytes, before, stringBytes.length);
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}
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public static String generateAsciiString(int n) {
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ThreadLocalRandom random = ThreadLocalRandom.current();
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StringBuilder sb = new StringBuilder(n);
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for (int i = 0; i < n; i++) {
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int ascii = random.nextInt(128);
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sb.append((char) ascii);
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}
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return sb.toString();
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}
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public static String generateUTF8String(int n) {
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ThreadLocalRandom random = ThreadLocalRandom.current();
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StringBuilder sb = new StringBuilder(n);
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for (int i = 0; i < n; i++) {
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int codePoint;
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int probability = random.nextInt(100);
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if (probability < 85) {
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// 1-byte UTF-8 (ASCII range)
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// 0x0000 to 0x007F
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codePoint = random.nextInt(0x0080);
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} else if (probability < 95) {
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// 2-byte UTF-8
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// 0x0080 to 0x07FF
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codePoint = random.nextInt(0x0080, 0x0800);
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} else {
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// 3-byte UTF-8
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// 0x0800 to 0xFFFF
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do {
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codePoint = random.nextInt(0x0800, 0x10000);
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// Skip surrogate pairs (0xD800-0xDFFF)
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} while (codePoint >= 0xD800 && codePoint <= 0xDFFF);
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}
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sb.appendCodePoint(codePoint);
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}
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return sb.toString();
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}
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}

‎build-tools/src/main/java/org/elasticsearch/gradle/testclusters/ElasticsearchNode.java‎

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// Limit the number of allocated processors for all nodes in the cluster by default.
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// This is to ensure that the tests run consistently across different environments.
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String processorCount = shouldConfigureTestClustersWithOneProcessor() ? "1" : "2";
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if (getVersion().onOrAfter("7.6.0")) {
1410+
if (getVersion().onOrAfter("7.4.0")) {
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baseConfig.put("node.processors", processorCount);
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} else {
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baseConfig.put("processors", processorCount);

‎docs/changelog/135886.yaml‎

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pr: 135886
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summary: Provide defaults for index sort settings
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area: Mapping
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type: bug
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issues:
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- 129062

‎docs/changelog/136066.yaml‎

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pr: 136066
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summary: Simulate shards moved by explicit commands
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area: Allocation
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type: enhancement
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issues: []

‎docs/changelog/136119.yaml‎

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pr: 136119
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summary: Fix logsdb settings provider mapping filters
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area: Logs
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type: bug
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issues:
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- 136107

‎docs/reference/elasticsearch/mapping-reference/semantic-text.md‎

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}
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```
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## Querying `semantic_text` fields [querying-semantic-text-fields]
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You can query `semantic_text` fields using the following query types:
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- Match query: The recommended method for querying `semantic_text` fields. You can use [Query DSL](/reference/query-languages/query-dsl/query-dsl-match-query.md) or [ES|QL](/reference/query-languages/esql/functions-operators/search-functions.md#esql-match) syntax.
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<!--
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Refer to examples of match queries on `semantic_text` fields.
621+
-->
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- [kNN query](/reference/query-languages/query-dsl/query-dsl-knn-query.md): Finds the nearest vectors to a query vector using a similarity metric, mainly for advanced or combined search use cases.
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<!--
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Refer to examples of kNN queries on `semantic_text` fields.
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-->
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- [Sparse vector query](/reference/query-languages/query-dsl/query-dsl-sparse-vector-query.md): Executes searches using sparse vectors generated by a sparse retrieval model such as [ELSER](docs-content://explore-analyze/machine-learning/nlp/ml-nlp-elser.md).
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<!--
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Refer to examples of sparse vector queries on `semantic_text` fields.
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-->
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- [Semantic query](/reference/query-languages/query-dsl/query-dsl-semantic-query.md): We don't recommend this legacy query type for _new_ projects, because the alternatives in this list enable more flexibility and customization. The `semantic` query remains available to support existing implementations.
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<!--
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Refer to examples of semantic queries on `semantic_text` fields.
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-->
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## Troubleshooting semantic_text fields [troubleshooting-semantic-text-fields]
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If you want to verify that your embeddings look correct, you can view the

‎docs/reference/elasticsearch/mapping-reference/sparse-vector.md‎

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* The tokens that are kept are frequent enough and have significant scoring.
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* Very infrequent tokens that may not have as high of a score are removed.
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## Accessing `dense_vector` fields in search responses
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## Accessing `sparse_vector` fields in search responses
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```{applies_to}
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stack: ga 9.2
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serverless: ga
102102
```
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104-
By default, `dense_vector` fields are **not included in `_source`** in responses from the `_search`, `_msearch`, `_get`, and `_mget` APIs.
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By default, `sparse_vector` fields are **not included in `_source`** in responses from the `_search`, `_msearch`, `_get`, and `_mget` APIs.
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This helps reduce response size and improve performance, especially in scenarios where vectors are used solely for similarity scoring and not required in the output.
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To retrieve vector values explicitly, you can use:

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